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A Novel Framework for Complex Networks and Chronic Diseases

  • Philippe J. Giabbanelli
Part of the Studies in Computational Intelligence book series (SCI, volume 424)

Abstract

Complex networks have provided a wealth of information regarding infectious diseases, for example by understanding how the network structure impacts the basic reproduction number or immunization strategies. However, researchers have struggled to translate this knowledge to chronic diseases, where social networks are at play but broad societal factors also have an important role. This translation is becoming urgent given the increasing prevalence, and the escalating healthcare costs, of conditions such as obesity. In this paper,we provide a mathematical framework that enables researchers to represent both the network and societal aspects of chronic disease, thereby facilitating this translation effort. Our framework uses Complex Networks to represent the population,where influences between neighboring nodes are modelled through Fuzzy Cognitive Maps that account for societal effects. Applying our framework to real-world cases, possibly through processes such as Group Model Building, may facilitate the better direction of policy towards the management of chronic diseases.

Keywords

Complex Network Cellular Automaton Social Determinant Basic Reproduction Number Immunization Strategy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Philippe J. Giabbanelli
    • 1
    • 2
  1. 1.MoCSSy Program, Interdisciplinary Research in the Mathematical and Computational Sciences (IRMACS) CentreSimon Fraser UniversityBurnabyCanada
  2. 2.Dept. of Biomedical PhysiologySimon Fraser UniversityBurnabyCanada

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